Wireless networks are employed for communication between various devices, such as cell phones and computers. Digitally modulated signals such as binary phase shift keyed and quadrature phase shift keyed signals are transmitted between nodes of the network. Examples include satellite communications networks where terminals transmit through satellite transponders, terrestrial systems where terminals transmit through repeating towers, and indoor local area networks where terminals transmit through central repeating elements.
Computer elements connected to these networks provide a variety of user services. Examples include telephone traffic with digital voice encoding, video conferencing, local and wide area computer network connectivity, and internet service. In such applications, it is desirable to maximize the network traffic capacity in a given bandwidth in the presence of interference and noise. To that end, a variety of modulation and coding schemes exist for efficiently partitioning the network elements into communication channels.
For example, frequency domain multiple access (FDMA) schemes assign each network terminal to a separate, non-overlapping frequency band. Time domain multiple access (TDMA) schemes assign each terminal to a separate non-overlapping time slot. Code division multiple access (CDMA) schemes assign each terminal to a separate modulating waveform so that the cross correlation between each terminal is negligible. Orthogonal frequency division multiplexing (OFDM) schemes break up a single wideband channel into many narrowband channels. Each channel transmits a small piece of information on a different subcarrier that together with the other channels comprises a larger block of information for a single user. The bands are selected so adjacent bands do not interfere with each other.
New, emerging wireless networking systems based on OFDM, networking standard 802.11, and multicarrier code division multiple access (MC-CDMA) are increasing in popularity. The increased number of wireless local area networks deployed in the likes of offices, apartment buildings, homes, and dormitories increases the potential for performance degradation due to multiuser interference (sometimes referred to as multi-access interference) when the systems are operating simultaneously in the same frequency band with similar modulation and spreading methods.
More specifically, a real world multiuser system includes a number of independent users simultaneously transmitting signals. Each of these transmissions are associated with real-time problems of multipath and multiuser interference that manifest in each of the received signals. Multipath occurs when a signal proceeds to its intended receiver along not one but many paths so that the receiver encounters echoes having different and randomly varying delays and amplitudes. Same-system interference refers to signals received from other users in the same system. In addition, where two or more networks are visible to the receiver, cross-system interference refers to signals received from other network systems.
A multiuser detection (MUD) receiver can be used to jointly demodulate co-channel interfering digital signals. In general, MUD refers to the detection of data in non-orthogonal multiplexes. MUD processing increases the number of information bits available per chip or signaling dimension for interference limited systems. Optimal MUD based on the maximum likelihood principle operates by comparing the received signal with the entire number of possibilities that may have occurred at the ensemble of transmitters, to give rise to the waveform received at the receiver. After implementing such a comparison, the optimal MUD chooses the most likely possibility as the estimate of the transmitted symbols from all transmitters.
However, for multiuser detectors that examine a larger capacity of signal, the computations are complex and time-consuming, thus making real-time operation impractical. Reduced complexity approaches based on conventional tree-pruning algorithms help to some extent. However, performance of such multiuser detection algorithms degrades as the parameter M (pruning factor) is decreased, but M governs the number of computations required. Thus, to combat improper pruning, basic tree-pruning must ensure that M is large enough. As a result, conventional pruning methods are still associated with increased complexity, particularly when the number of interfering signals is moderate to large.
In some cases, the multiuser interference can be so severe that the signals are not detectable by conventional single-user demodulation (such as matched filters, which typically treat other-user interference as noise), conventional multiuser demodulation (such as optimal MUD, or minimum mean-square error MUD), and iterative MUD decoding methods (such as turboMUD). Same-system interference cancellation techniques can be used to generally improve the performance of multiuser communication systems, where the number of users is less than the dimensions available to the common channel. However, conventional multiuser detection techniques are unable to demodulate co-channel signals in an overloaded environment (when the number of users is greater than the number of dimensions available to the common channel), or when signals of more than one network system are received (cross-system interference).
What is needed, therefore, are techniques that enable interference cancellation in multicarrier communication systems, and particularly in systems where two or more networks are visible. Such techniques would increase the allowable number of simultaneous network users without significant degradation of performance. Such techniques would also facilitate the implementation of multiple co-located wireless networks without pre-installation knowledge of any existing systems or coordination between networks.